Patients with the same cancer diagnosis may experience very distinct disease progressions and treatment responses. These differences between patients have been associated with their degree of intra-tumor heterogeneity-the genetic, epigenetic, spatial, and environmental differences between the tumor cells. Characterizing the genetic and epigenetic states of different tumor cells is key to understanding how intra-tumor heterogeneity influences tumor progression, expansion, metastasis, and treatment response. Recent advances in single-cell RNA sequencing and spatial transcriptomics (which shows the spatial distribution of RNA molecules within a tissue sample) provide new opportunities to study intra-tumor heterogeneity in higher resolution. Dr. Ma's research aims to characterize intra-tumor heterogeneity in terms of specific genetic and epigenetic measures, and eventually develop 3D tumor models that capture this heterogeneity across multiple cancer types. Dr. Ma received her BS from Zhejiang University and her PhD in computational biology from Carnegie Mellon University.

The proposed computational methods will be based on previous methods developed in the group. Dr. Ma will develop a better method for identifying tumor clones for spatially resolved transcriptomics (SRT) data using both copy number and allele information using HMM and HMRF. She will adapt optimal transport frameworks and include biological networks as prior knowledge for integrating epigenetic data with SRT and between SRT slices to construct 3D spatial tumor multi-omics models.